Paper ID: 2305.09534

MetaSRL++: A Uniform Scheme for Modelling Deeper Semantics

Fritz Hohl, Nianheng Wu, Martina Galetti, Remi van Trijp

Despite enormous progress in Natural Language Processing (NLP), our field is still lacking a common deep semantic representation scheme. As a result, the problem of meaning and understanding is typically sidestepped through more simple, approximative methods. This paper argues that in order to arrive at such a scheme, we also need a common modelling scheme. It therefore introduces MetaSRL++, a uniform, language- and modality-independent modelling scheme based on Semantic Graphs, as a step towards a common representation scheme; as well as a method for defining the concepts and entities that are used in these graphs. Our output is twofold. First, we illustrate MetaSRL++ through concrete examples. Secondly, we discuss how it relates to existing work in the field.

Submitted: May 16, 2023